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Texture‐based image segmentation applied to the quantification of superficial sand in salmonid river gravels
Author(s) -
Carbonneau Patrice E.,
Bergeron Normand E.,
Lane Stuart N.
Publication year - 2005
Publication title -
earth surface processes and landforms
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.294
H-Index - 127
eISSN - 1096-9837
pISSN - 0197-9337
DOI - 10.1002/esp.1140
Subject(s) - texture (cosmology) , sediment , segmentation , geology , sampling (signal processing) , scanner , artificial intelligence , computer science , image (mathematics) , computer vision , geomorphology , filter (signal processing)
The presence of ne sediment in river gravels is widely recognized as being detrimental to salmonid habitat quality. In order to facilitate quantication of sand presence at larger scales, this paper presents an application of image processing allowing for rapid and accurate assessments of supercial sand presence in dry exposed uvial gravels. Images for the process are acquired with a 35 mm SLR lm camera and then scanned with a desktop scanner. Texture‐based segmentation is then applied to differentiate between sand and clast areas. Results show that the method is accurate and therefore it offers an alternative to bulk sampling in cases where rapid assessments of sand presence are required. Copyright © 2005 John Wiley & Sons, Ltd.